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//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
//g++ -O3 -g0 -DNDEBUG sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
// -DNOGMM -DNOMTL -DCSPARSE
// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
#ifndef SIZE
#define SIZE 10000
#endif
#ifndef DENSITY
#define DENSITY 0.01
#endif
#ifndef REPEAT
#define REPEAT 1
#endif
#include "BenchSparseUtil.h"
#ifndef MINDENSITY
#define MINDENSITY 0.0004
#endif
#ifndef NBTRIES
#define NBTRIES 10
#endif
#define BENCH(X) \
timer.reset(); \
for (int _j=0; _j<NBTRIES; ++_j) { \
timer.start(); \
for (int _k=0; _k<REPEAT; ++_k) { \
X \
} timer.stop(); }
#ifdef CSPARSE
cs* cs_sorted_multiply(const cs* a, const cs* b)
{
cs* A = cs_transpose (a, 1) ;
cs* B = cs_transpose (b, 1) ;
cs* D = cs_multiply (B,A) ; /* D = B'*A' */
cs_spfree (A) ;
cs_spfree (B) ;
cs_dropzeros (D) ; /* drop zeros from D */
cs* C = cs_transpose (D, 1) ; /* C = D', so that C is sorted */
cs_spfree (D) ;
return C;
}
#endif
int main(int argc, char *argv[])
{
int rows = SIZE;
int cols = SIZE;
float density = DENSITY;
EigenSparseMatrix sm1(rows,cols);
DenseVector v1(cols), v2(cols);
v1.setRandom();
BenchTimer timer;
for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
{
fillMatrix(density, rows, cols, sm1);
// dense matrices
#ifdef DENSEMATRIX
{
std::cout << "Eigen Dense\t" << density*100 << "%\n";
DenseMatrix m1(rows,cols);
eiToDense(sm1, m1);
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
v2 = m1 * v1;
timer.stop();
std::cout << " a * v:\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
v2 = m1.transpose() * v1;
timer.stop();
std::cout << " a' * v:\t" << timer.value() << endl;
}
#endif
// eigen sparse matrices
{
std::cout << "Eigen sparse\t" << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
BENCH(for (int k=0; k<REPEAT; ++k) v2 = sm1 * v1;)
std::cout << " a * v:\t" << timer.value() << endl;
BENCH(for (int k=0; k<REPEAT; ++k) { asm("#mya"); v2 = sm1.transpose() * v1; asm("#myb"); })
std::cout << " a' * v:\t" << timer.value() << endl;
}
// {
// DynamicSparseMatrix<Scalar> m1(sm1);
// std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/float(m1.rows()*m1.cols())*100 << "%\n";
//
// BENCH(for (int k=0; k<REPEAT; ++k) v2 = m1 * v1;)
// std::cout << " a * v:\t" << timer.value() << endl;
//
// BENCH(for (int k=0; k<REPEAT; ++k) v2 = m1.transpose() * v1;)
// std::cout << " a' * v:\t" << timer.value() << endl;
// }
// GMM++
#ifndef NOGMM
{
std::cout << "GMM++ sparse\t" << density*100 << "%\n";
//GmmDynSparse gmmT3(rows,cols);
GmmSparse m1(rows,cols);
eiToGmm(sm1, m1);
std::vector<Scalar> gmmV1(cols), gmmV2(cols);
Map<Matrix<Scalar,Dynamic,1> >(&gmmV1[0], cols) = v1;
Map<Matrix<Scalar,Dynamic,1> >(&gmmV2[0], cols) = v2;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
gmm::mult(m1, gmmV1, gmmV2);
timer.stop();
std::cout << " a * v:\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
gmm::mult(gmm::transposed(m1), gmmV1, gmmV2);
timer.stop();
std::cout << " a' * v:\t" << timer.value() << endl;
}
#endif
// MTL4
#ifndef NOMTL
{
std::cout << "MTL4\t" << density*100 << "%\n";
MtlSparse m1(rows,cols);
eiToMtl(sm1, m1);
mtl::dense_vector<Scalar> mtlV1(cols, 1.0);
mtl::dense_vector<Scalar> mtlV2(cols, 1.0);
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
mtlV2 = m1 * mtlV1;
timer.stop();
std::cout << " a * v:\t" << timer.value() << endl;
timer.reset();
timer.start();
for (int k=0; k<REPEAT; ++k)
mtlV2 = trans(m1) * mtlV1;
timer.stop();
std::cout << " a' * v:\t" << timer.value() << endl;
}
#endif
std::cout << "\n\n";
}
return 0;
}
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